Tag: autonomous vehicle

Overview:
Success of numerous long-term robotic network missions in space, air, ground, and water is measured by the ability of the robots to operate for extended time in highly dynamic and potentially hazardous operating environments. The proposed work responds to the urgency for development of innovative mobile power distribution systems that lower deployment and operating costs, while simultaneously increasing mission efficiency, and supporting the network’s need to be responsive to changing physical conditions. The overall CAREER goal is to develop a power distribution system that responds to individual robot needs, as well as, overall robotic network goals to guarantee persistence of long-term operation in uncertain and unstructured environments.

The proposed work is informed by the hypothesis that network persistence hinges on the ability to establish stable energy transfer cycles necessary to accomplish coverage specifications, while simultaneously dealing with physical and environmental constraints. To test this hypothesis and as an example of such a system, this work will focus on creating a reliable autonomous recharging system for autonomous underwater vehicles (AUVs) that enables continuous real-time marine observation and data collection in the presence of continuously changing underwater environmental circumstances. The key challenges are two-fold: there are fundamental hardware challenges connected to energy transfer in the harsh underwater environment, but more importantly there are basic network science needs that are novel to a mobile power network. The specific research thrusts for this CAREER work include: 1) Task and Energy Routing Scheduling for Persistent Mission Planning. 2) Efficient Network Path Planning and Coordination to Accomplish Persistent Mission Plan. 3) Experimental Validation through Test-bed Development. 4) Design-based, Research-integrated Education Plan for Broadening Underrepresented Participation in STEM.

Intellectual Merit:
This project builds a roadmap to achieve robust continuous marine autonomy that advances unmanned marine systems ability to perform autonomous long-term missions. More specifically the proposed work will provide: 1) resource based task scheduling, 2) path planning formation for mission and charging, and 3) integration tools for testing. Expected outcomes will overcome the current challenge of significant interruptions during underwater missions due to battery limitations and recharging needs. Through this CAREER proposal, the Pl will establish the theoretical, computational, and experimental foundation for mobile power delivery and onsite recharging capability for autonomous underwater vehicles (AUVs). The developed power distribution system will be able to reconfigure itself depending on the scope of the mission, as well as, the energy consumption needs of the network, the number of operational AUVs and required operation time, recharging specifications, communication and localization means, and environmental variables.

Such a system will play a vital role in real-time controlled applications across multiple disciplines, such as: sensor networks, robotics, and transportation systems where limited power resources and unknown environmental dynamics pose major constraints. All developed tools will be suited for the capabilities of not only low-cost AUVs with limited sensing and computational resources, but also high-tech AUVs with state of the art sensor packages.

Broader Impacts:
The developed active power distribution system focuses on underwater scenarios, but will be transferrable to space, air, and ground missions as well. This type of feasible power distribution solution can be used to optimize: 1) immediate high-risk disaster recovery missions like the Fukushima nuclear plant accident; 2) search missions that require vast underwater inspection and detection like the Malaysia MH370 passenger aircraft; and 3) long-term space observation and monitoring like that of the lunar skylight or Europa space mission. The findings from this project will be disseminated through publications, software sharing, and technology commercialization. The project provides interdisciplinary training opportunities for graduate, undergraduate, and pre-college students, including those from underrepresented groups. Research activities will be integrated with education through curriculum development, outreach and improved GUPPIE design.

Overview:
Correctly, the 2009 Roadmap for US Robotics report predicted that robotics technology would transform the future of the US workforce and households. From Roomba vacuum cleaners to Wii video games, we increasingly see robotic technology in work spaces and homes. Yet, the US continues to lag behind China, South Korea, Japan, and European Union in its investment in robotics research and education. The Next Generation Science Standards for Today’s Students and Tomorrow’s Workforce responds to this critical need by providing a curricular framework for using crosscutting concepts and disciplinary ideas that: have broad importance across science and engineering disciplines; are taught around a key organizing concept (like health or water) and use key tool (pedagogical platform); have a significant context for students and are explicitly connected to societal needs; and are teachable and learnable over multiple grades. Informed by this framework, our proposed NRI aims to develop, test, and assess two co-robotic platforms with high impact potential and longevity as a pedagogical platform (use is applicable from 4th grade through graduate school learning). Two unique robotics educational platforms will be used to teach 6th-8th grade: an educational underwater glider called GUPPIE and a surface electromyography (sEMG)- controlled manipulator called Neu-pulator. Both of these platforms can be categorized as co-robot and cost less than $1000. GUPPIE is an unmanned vehicle that has application in monitoring and inspection of the environment and can be used to introduce students to the application of robots as co-explorers in everyday life. Neu-pulator is a human-interactive robot that uses electrical activity of human muscles to move a manipulator. It introduces students to assistive robots, which are a class of co-robots that aim to amplify or compensate for human capabilities. We hypothesize that meaningful contexts and hands-on learning with co-robotic platforms will broaden impact to diverse audiences and increase interest in critical STEM areas. The overall goal of the proposed NRI is to develop and evaluate the use of co-robotic platforms in learning contexts that are socially meaningful, especially for underrepresented students (female students from rural, low socioeconomic areas in the Upper Peninsula of Michigan). Our specific objectives are to: 1) Optimize Michigan Tech’s co-robotic platform designs for teaching STEM concepts. 2) Develop educational activities/curriculum utilizing Michigan Tech’s co-robotic platforms. 3) Investigate the co-robotic platforms effectiveness in engaging students in STEM learning.

Intellectual Merit:
The proposed work will develop a pedagogical platform and evaluation method that can be easily translated for classroom practice from grades 4th-12th and in undergraduate to graduate degree programs. Training teachers in platform use during teacher workshops will help schools respond to and integrate new science standards – efficiently and effectively using meaningful contexts. Continued online training and modules will be available to broadly disseminate platform applications for informal and formal learning contexts. The hardware development and programming of co-robots will teach critical analytical thinking. The nature of co-robotic platforms, on the other hand, will inspire students to become integrative designers. By exercising both analytical thinking and design skills, these co-robotic platforms will improve students’ ability for creative problem solving, and ultimately increase individual motivation for pursuing STEM academic and career pathways. The project will produce research that compares the effectiveness of mission-based and application-based robotics activities for engaging students in STEM.

Project Description and Research Objectives:
From large scale electric power grids and microgrids down to small scale electronics, power networks are typically deployed using a fixed infrastructure architecture that cannot expand or contract without significant human intervention. Mobile, monolithic power systems exist but are also not readily scalable to exploit surrounding power sources and storage devices. However, if a power network is constructed from physically independent and autonomous building blocks, then it would be infinitely reconfigurable and adaptable to changing needs and environments. The aim of this project is to integrate vehicle robotics with intelligent power electronics to create self-organizing, ad-hoc, hybrid AC/DC microgrids. The main benefits of this system would be the establishment and operation of an electrical power networks independent of human interaction and can adapt to changing environments, resource and mission. In the context of U.S. Naval platforms, this autonomous electrical network could be used in land, air or sea systems.

The focus of this work will be on land based autonomous microgrid systems, but the fundamental theory developed may be applicable to air and sea based systems as well. Investigators at Michigan Technological University have developed initial hardware and testbeds to study this problem. However, a more detailed theoretical foundation is needed to be developed to apply autonomous microgrids to a wide variety of operational scenarios with various resources. It is also hypothesized that given the flexibility of this approach that it could be equally applied over a vast scale of energy assets. A microgrid that grows in situ from 10 s to 100 s to 1000 s of energy assets can be equally managed, controlled and optimized through the highly scalable approach proposed in this project.

These applications are examples of the critical need for autonomous mobile microgrid capable of operating in highly dynamic and potentially hazardous environments. Our overall goal is to create a scalable architecture to develop a system that accounts for uncertainty in predictions and disturbances, is redundant, requires minimal communication between agents, provides real-time guarantees on the performance of path planning, and reaches the targets while making electrical connections. Such architecture provide a coherent layout for the interconnection between different disciplines on this topic and minimizes the integration concerns for future developments.

Description of the Proposed Work:
• Microgrid Planning and Control
• Microgrid Topology and Optimization
• Electrical Components and Power Flow
• Game-Theoretic Control
• Physical Autonomous Positioning and Connections

The current challenge impeding advances in the U.S. Navy’s mobility is significant interruptions during undersea missions. Missions such as studying arctic physical environments; understanding the effects of sound on marine mammals; submarine detection and classification; and mine detection and neutralization in both the ocean and littoral environment require persistent operation of unmanned systems in challenging and dynamic environments. The proposed work will create an architecture that integrates three elements of energy, communication, and docking to guarantee undersea persistence where limited power resources and unknown environmental dynamics pose major constraints. The architecture will take into account: the number of operational AUVs required for different operation periods, recharging specifications, communication and localization means, and environmental variables.

The overall goal of this project is: to develop a mobile power delivery system that lowers deployment and operating costs while simultaneously increasing network efficiency and response in dynamic and often dangerous physical conditions. The aim is to create network optimization and formation strategies that will enable a mobile power deliver system to meet overall mission specifications by: 1) reconfiguring itself depending on the number of operational AUVs and; 2) responding to energy consumption needs of the network, situational condition, and environmental variables. The outcome of this work will be a theoretical, computational, and experimental roadmap for building and implementing an autonomous distributed system with mobile power delivery and onsite recharging capability. This roadmap will address fundamental hardware and network science challenges. The long-term outcome of this work will be a persistent and stealthy large area presence of AUV fleets able to perform undersea Navy missions by accurately and autonomously responding to energy needs, situational dynamics and environmental variables.

Big disasters almost always result in big power failures. Not only do they take down the TV and fridge, they also wreak havoc with key infrastructure like cell towers. That can delay search and rescue operations at a time when minutes count.

Now, a team led by Nina Mahmoudian of Michigan Technological University has developed a tabletop model of a robot team that can bring power to places that need it the most.

“If we can regain power in communication towers, then we can find the people we need to rescue,” says Mahmoudian, an assistant professor of mechanical engineering–engineering mechanics. “And the human rescuers can communicate with each other.”

Unfortunately, cell towers are often located in hard-to-reach places, she says. “If we could deploy robots there, that would be the first step toward recovery.”

The team has programmed robots to restore power in small electrical networks, linking up power cords and batteries to light a little lamp or set a flag to waving with a small electrical motor. The robots operate independently, choosing the shortest path and avoiding obstacles, just as you would want them to if they were hooking up an emergency power source to a cell tower. To view the robots in action, see the video posted on Mahmoudian’s website.

“Our robots can carry batteries, or possibly a photovoltaic system or a generator,” Mahmoudian said. The team is also working with Wayne Weaver, the Dave House Associate Professor of Electrical Engineering, to incorporate a power converter, since different systems and countries have different electrical requirements (as anyone who has ever blown out a hair dryer in Spain can attest).

In addition to disaster recovery, their autonomous power distribution system could have military uses, particularly for special forces on covert missions. “We could set up power systems before the soldiers arrive on site, so they wouldn’t have to carry all this heavy stuff,” said Mahmoudian.

The team’s next project is in the works: a full-size, working model of their robot network. Their first robot is a tank-like vehicle donated by Michigan Tech’s Keweenaw Research Center. “This will let us develop path-planning algorithms that will work in the real world,” said Mahmoudian.

The robots could also recharge one another, an application that would be as attractive under the ocean as on land.

During search missions like the one conducted for Malaysia Airlines Flight 370, the underwater vehicles scanning for wreckage must come to the surface for refueling. Mahmoudian envisions a fleet of fuel mules that could dive underwater, charge up the searching robot and return to the mother ship. That way, these expensive search vehicles could spend more time looking for evidence and less time traveling back and forth from the surface.

This research is focused on development of innovative practical solutions for control of individual and multiple unmanned underwater vehicles (UUVs) and address challenges such as underwater communication and localization that currently limit UUV use. More specifically, the Nonlinear and Autonomous Systems Laboratory (NAS Lab) team are developing a rigorous framework for analyzing and controlling underwater gliders (UGs) in harsh dynamic environments for the purpose of advancing efficient, collaborative behavior of UUVs.

Underwater gliders are now utilized for much more than long-term, basin-scale oceanographic sampling. In addition to environmental monitoring, UGs are increasingly depended on for littoral surveillance and other military applications. This research will facilitate the transition between academic modeling/simulation problem solving approach to real-world Navy applications. The importance of this research is evident in the Littoral BattleSpace Sensing (LBS) Program contract at the Naval Space and Naval Warfare Systems Command for 150 underwater gliders, designated the LBS-G. These gliders will be operated by the Navy in forward areas to rapidly assess and exploit environmental characteristics to improve the maneuvering of ships and submarines and advance the performance of fleet sensors.

Research results will provide the coordination tools necessary to enable the integration of these efficient and quiet vehicles as part of a heterogeneous network of autonomous vehicles capable of performing complex, tactical missions. The objective is to develop practical, energy-efficient motion control strategies for both individual and multiple UGs while performing in inhospitable, uncertain, and dynamic underwater environments.

The specific goals of this project are twofold. The first goal is to design and fabricate a fleet of low-cost highly maneuverable lightweight underwater gliders. The second goal is to evaluate the capability of the single and multiple developed UGs in littoral zones. The proposed work will develop UGs that would share the buoyancy-driven concept with the first generation of gliders called “legacy gliders.” However, the NAS Lab UGs will be smaller in size, lighter in weight, and lower in price than legacy gliders. This will result in more affordable and novel UG applications. Moreover, the NAS Lab design to development approach allows for technological innovation that overcomes known challenges and responds to unexpected needs that arise during testing. Therefore, the significance of this research is that it will enable implementation of recently developed efficient motion planning algorithms, multi-vehicle coordination algorithms, and extension of these algorithms in realistic conditions where absolute location and orientation of each vehicle is not known and the time-varying flow field is not locally determined.

Introduction
There is a wide range of hydraulic extending-boom and knuckle-boom cranes in use on marine vessels. These cranes are often used in dynamic motion environments for cargo transfer and small boat handling. The ability to safely launch and recover small boats in elevated sea states for naval, Coast Guard and oceanographic purposes is currently a focus of investigation within these communities.

The purpose of this investigation is to extend the research begun under SBIR topic N06-
057, “Cargo Transfer from Offshore Supply Vessels to Large Deck Vessels” to improve the performance of hydraulic marine cranes in the dynamic offshore environment. In addition, the lessons learned during the development of the Integrated Rider Block Tagline System (IRBTS), the Platform Motion Compensation System (PMC) and the Pendulation Control System (PCS) for the rigid-boom, level-luffing marine cranes used for container handling on sealift ships will be incorporated into a final integrated, modular kit to improve cargo transfer with these extending-boom and knuckle-boom cranes.

Phase II Technical Objectives
The goal of Phase II is to develop and demonstrate a modular solution for crane pendulation and motion control suitable for a wide range of existing U.S. Navy ship cranes. Phase I clearly showed that pendulation control can be modularized by implementing ship motion cancellation using the crane’s existing drive system and active load damping using a retrofit damping device. In that work, a specific crane design was considered and the study was strictly proof-of-concept through simulation.

Phase II focuses on identifying the range of cranes for which the modular approach is feasible, developing the analysis and design work flow needed to design and deploy the modular solution, and demonstrating both the process and the performance on a particular crane. The incremental technical objectives of Phase II are listed below.

1. The analysis and design process for implementing modular pendulation and motion control on any crane,
2. The development of a modular crane control system (MCCS) “kit” including refinement of the key subsystems (sensors, actuation, algorithms),
3. A phased demonstration of MCCS using 1/12th and larger scale testbeds.

At the conclusion of Phase II, the objective is to have a fully functioning MCCS system demonstrating ship motion cancellation, active payload damping on an articulated crane similar to those currently deployed on numerous U.S. Navy and civilian ships. The Phase II Option will focus this development on a design that can be implemented on the hydraulic extending-boom crane, currently proposed for use on the JHSV.

Dr. Vaughn has joined Michigan Tech as a research professor after retiring from Sandia National Laboratories. His research expertise is in the area of mechanical and electromechanical design, stress analysis, dynamics, and innovative applications. He has over 10 patents, and has been the lead on a broad array of projects for the military.

Dr. Mahmoudian’s general research interests lie in the area of dynamics, stability, and control of nonlinear systems. Specifically, she is interested in dynamic modeling, motion planning, and developing cooperative control algorithms to autonomous vehicles. Design and control of autonomous vehicles based on the principles used by nature is another area of interest. She works on developing analytical and computational tools for the cooperative control of a network of autonomous vehicles in complex environment using nonlinear control and stochastic analysis. The application will be for air, ground, and sea autonomous vehicles.

Michigan Technological University is an Equal Opportunity Educational Institution/Equal Opportunity Employer, which includes providing equal opportunity for protected veterans and individuals with disabilities.